Integrated Metabolome and Microbiome Analysis Reveals the Regulatory Effects of Fermented Soybean Meal on the Gut Microbiota of Late Gestation

Late gestation is a critical period for regulating maternal peripartum physiological metabolism and gut microbiota balance. Fermented diets have been widely recognized as effective exogenous nutritional interventions capable of modulating the maintenance of gut microbiota homeostasis. However, the mechanism through which fermented diets modulate the gut microbiota in late-gestation remains poorly understood. In this study, an in vitro fermentation model combined with chemical composition analysis, untargeted metabolomics, and high-throughput sequencing was employed to investigate the metabolic alterations during soybean meal (SBM) fermentation and the regulatory effects of fermented soybean meal (FSBM) on gut microbiota of late-gestation sows. The findings revealed that fermentation significantly increased the levels of crude protein, lactic acid, acid-soluble protein, lysine, histidine, and total amino acids of SBM. Conversely, the levels of crude fiber, NDF, ADF, starch, and non-starch polysaccharides were markedly reduced, compared to the unfermented group. A total of 941 differentially expressed metabolites were identified between SBM and FSBM. Specifically, FSBM elevated the levels of lactic acid, L-pyroglutamic acid, 2-aminoisobutyric acid, and tyrosine, while substantially decreasing the levels of raffinose, sucrose, and stachyose. Metabolic pathway analysis identified glutathione metabolism, tyrosine metabolism, and pantothenate and coenzyme A (CoA) biosynthesis as the key pathways involved in SBM fermentation. In vitro fermentation experiments demonstrated that FSBM substantially increased the production of short-chain fatty acids (SCFAs) and notably increased the relative abundance of sows gut commensal Lactobacillus and Limosilactobacillus in late gestation. In summary, this study demonstrated that co-fermentation with bacteria and enzymes pretreatment of soybean meal reduced fiber components and enriched bioactive metabolites, optimizing intestinal microbial composition and increasing SCFA production in late-pregnant period. The present study provides novel insights into the regulatory effects of fermented diets on gut microbiota in late-gestation period from the perspectives of nutritional composition and metabolites.

Authors

Institutions

Publication Details

Journal
Fermentation
Published
2025-05-31
DOI
https://doi.org/10.3390/fermentation11060315
Citations
1
Primary Topic
Proteins in Food Systems
Type
article
Field-Weighted Citation Impact
1.16

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrated Metabolome and Microbiome Analysis Reveals the Regulatory Effects of Fermented Soybean Meal on the Gut Microbiota of Late Gestation

Hua Yang, Cheng Wang, Yingping Xiao, Yantao Li et al.
1 citations
Fermentation
Proteins in Food Systems
1.16
article

Integrated Metabolome and Microbiome Analysis Reveals the Regulatory Effects of Fermented Soybean Meal on the Gut Microbiota of Late Gestation

Hua Yang, Cheng Wang, Yingping Xiao, Yantao Li, Yushi Chen, Ying Ren, Lele Fu
article en
1 citations

Abstract

Late gestation is a critical period for regulating maternal peripartum physiological metabolism and gut microbiota balance. Fermented diets have been widely recognized as effective exogenous nutritional interventions capable of modulating the maintenance of gut microbiota homeostasis. However, the mechanism through which fermented diets modulate the gut microbiota in late-gestation remains poorly understood. In this study, an in vitro fermentation model combined with chemical composition analysis, untargeted metabolomics, and high-throughput sequencing was employed to investigate the metabolic alterations during soybean meal (SBM) fermentation and the regulatory effects of fermented soybean meal (FSBM) on gut microbiota of late-gestation sows. The findings revealed that fermentation significantly increased the levels of crude protein, lactic acid, acid-soluble protein, lysine, histidine, and total amino acids of SBM. Conversely, the levels of crude fiber, NDF, ADF, starch, and non-starch polysaccharides were markedly reduced, compared to the unfermented group. A total of 941 differentially expressed metabolites were identified between SBM and FSBM. Specifically, FSBM elevated the levels of lactic acid, L-pyroglutamic acid, 2-aminoisobutyric acid, and tyrosine, while substantially decreasing the levels of raffinose, sucrose, and stachyose. Metabolic pathway analysis identified glutathione metabolism, tyrosine metabolism, and pantothenate and coenzyme A (CoA) biosynthesis as the key pathways involved in SBM fermentation. In vitro fermentation experiments demonstrated that FSBM substantially increased the production of short-chain fatty acids (SCFAs) and notably increased the relative abundance of sows gut commensal Lactobacillus and Limosilactobacillus in late gestation. In summary, this study demonstrated that co-fermentation with bacteria and enzymes pretreatment of soybean meal reduced fiber components and enriched bioactive metabolites, optimizing intestinal microbial composition and increasing SCFA production in late-pregnant period. The present study provides novel insights into the regulatory effects of fermented diets on gut microbiota in late-gestation period from the perspectives of nutritional composition and metabolites.

FermentationVol. 11(6)
Wuhan Polytechnic University (CN), ZheJiang Academy of Agricultural Sciences (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 21%
Proteins in Food Systems
1.16
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.